# Customization and extension of functionality¶

DataLad provides numerous commands that cover many use cases. However, there will always be a demand for further customization or extensions of built-in functionality at a particular site, or for an individual user. DataLad addresses this need with two mechanisms:

Plugins are a quick’n’dirty way to implement a single additional command with very little overhead. They are, however, not the method of choice for extending particular Datalad functionality, such as metadata extractor, or providing entire command suites for a specialized purpose. For all these scenarios extension packages are the recommended method.

## Plugins¶

A number of plugins are shipped with DataLad. This includes plugins which operate on a particular dataset, but also general functionality that can be used outside the context of a specific dataset. The following table provides an overview of plugins included in this DataLad release.

 add_readme add a README file to a dataset addurls Create and update a dataset from a list of URLs. check_dates Extension for checking dates within repositories. export_archive export a dataset as a compressed TAR/ZIP archive export_to_figshare export a dataset as a TAR/ZIP archive to figshare no_annex configure which dataset parts to never put in the annex wtf provide information about this DataLad installation

In previous versions of DataLad, plugins were invoked differently than regular DataLad commands, but they can now be called like any other command. The wtf plugin, for example, is exposed as

% datalad wtf


### Plugin detection¶

DataLad will discover plugins at three locations:

1. official plugins that are part of the local DataLad installation

2. system-wide plugins, provided by the local admin

The location where plugins need to be placed depends on the platform. On GNU/Linux systems this will be /etc/xdg/datalad/plugins, whereas on Windows it will be C:\ProgramData\datalad.org\datalad\plugins.

This default location can be overridden by setting the datalad.locations.system-plugins configuration variable in the local or global Git configuration.

3. user-supplied plugins, customizable by each user

Again, the location will depend on the platform. On GNU/Linux systems this will be \$HOME/.config/datalad/plugins, whereas on Windows it will be C:\Users\<username>\AppData\Local\datalad.org\datalad\plugins.

This default location can be overridden by setting the datalad.locations.user-plugins configuration variable in the local or global Git configuration.

Identically named plugins in latter location replace those in locations searched before. This can be used to alter the behavior of plugins provided with DataLad, and enables users to adjust a site-wide configuration.

### Writing own plugins¶

The best way to go about writing your own plugin, is to have a look at the source code of those include in DataLad. Writing a plugin a rather simple when following the following rules.

#### Language and location¶

Plugins are written in Python. In order for DataLad to be able to find them, plugins need to be placed in one of the supported locations described above. Plugin file names have to have a ‘.py’ extensions and must not start with an underscore (‘_’).

#### Skeleton of a plugin¶

The basic structure of a plugin looks like this:

from datalad.interface.base import build_doc, Interface

@build_doc
class MyPlugin(Interface):
"""Help message description (parameters will be added automatically)"""

_params_ = dict(
dataset=Parameter(
args=("-d", "--dataset"),
doc=""""specify the dataset to report on.
no dataset is given, an attempt is made to identify the dataset
based on the current working directory.""",
constraints=EnsureDataset() | EnsureNone()))

@staticmethod
@datasetmethod(name='my-plugin')
@eval_results
def __call__(dataset):
# Do things and yield status dicts.
pass



In this example, the plugin is called my-plugin. Any number of parameters can be added by extending both the _params_ dictionary and the signature of __call__. The help message for the plugin command is generated using the docstring of the plugin class and the _params_ dictionary.

#### Expected behavior¶

The plugin’s __call__ method must yield its results as a Python generator. Results are DataLad status dictionaries. There are no constraints on the number of results, or the number and nature of result properties. However, conventions exists and must be followed for compatibility with the result evaluation and rendering performed by DataLad.

The following property keys must exist:

“status”
{‘ok’, ‘notneeded’, ‘impossible’, ‘error’}
“action”
label for the action performed by the plugin. In many cases this could be the plugin’s name.

The following keys should exists if possible:

“path”
absolute path to a result on the file system
“type”
label indicating the nature of a result (e.g. ‘file’, ‘dataset’, ‘directory’, etc.)
“message”
string message annotating the result, particularly important for non-ok results. This can be a tuple with ‘logging’-style string expansion.

## Extension packages¶

As the name suggests, an extension package is a proper Python package. Consequently, there is a significant amount of boilerplate code involved in the creation of a new Datalad extension. However, this overhead enables a number of useful features for extension developers:

• extensions can provide any number of additional commands that can be grouped into labeled command suites, and are automatically exposed via the standard DataLad commandline and Python API
• extensions can define entry_points for any number of additional metadata extractors that become automatically available to DataLad
• extensions can define entry_points for their test suites, such that the standard datalad test command will automatically run these tests in addition to the tests shipped with Datalad core
• extensions can ship additional dataset procedures by installing them into a directory resources/procedures underneath the extension module directory

### Using an extension¶

A DataLad extension is a standard Python package. Beyond installation of the package there is no additional setup required.